A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
11don MSN
Machine learning model predicts serious transplant complications months before symptoms appear
A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...
Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.
XRP price is riding a wave of renewed altcoin momentum, and machine learning algorithms suggests further upside potential by March.
Researchers are using artificial intelligence to perfect the design of the vessels surrounding the super-hot plasma, optimize heating methods and maintain stable control of the reaction for ...
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